Triple
T35337855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quest for secure identity |
E1020511
|
entity |
| Predicate | thematicOppositionTo |
P133980
|
FINISHED |
| Object | fixed identity |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: fixed identity | Statement: [Quest for secure identity, thematicOppositionTo, fixed identity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thematicOppositionTo Context triple: [Quest for secure identity, thematicOppositionTo, fixed identity]
-
A.
oppositionTheme
chosen
Indicates that one entity thematically represents or embodies opposition or conflict in relation to another entity.
-
B.
typeOfOpposition
Indicates a relationship where one entity stands in opposition or contrast to another, such as being a rival, adversary, or countering force.
-
C.
symbolicOpposition
Indicates a relationship where one entity stands in conceptual or representational contrast to another, typically as an opposing symbol, idea, or sign.
-
D.
theoryOpposed
Indicates that one theory stands in opposition to, or conflicts with, another theory.
-
E.
opposition
Indicates a relationship in which one entity actively resists, disagrees with, or is positioned against another entity, idea, or action.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76debb4e08190be52d89b8af2392d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79533b88c8190934ec4cb21770e24 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.